{
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     "end_time": "2019-11-11T08:41:42.739561Z",
     "start_time": "2019-11-11T08:41:32.650538Z"
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       "      <td>WEIXIN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>CLEAR</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190812161211246748</td>\n",
       "      <td>2019/8/12 9:02:03</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>2019/11/4 2:28:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190811173211212918</td>\n",
       "      <td>2019/8/11 10:10:09</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
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       "      <td>2019/11/8 13:59:55</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190811170357210945</td>\n",
       "      <td>2019/8/11 9:08:28</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/10/3 22:06:22</td>\n",
       "      <td>2019/11/3 12:29:50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190708140722479876</td>\n",
       "      <td>2019/7/8 6:49:56</td>\n",
       "      <td>DUMIAO</td>\n",
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       "      <td>2019/11/8 7:42:58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 2:10:27</td>\n",
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       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190707190815458746</td>\n",
       "      <td>2019/7/7 11:25:09</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/10/8 1:57:58</td>\n",
       "      <td>2019/11/6 1:44:08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 1:06:16</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20190709110351508498</td>\n",
       "      <td>2019/7/9 3:38:39</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>2019/10/1 10:12:16</td>\n",
       "      <td>2019/11/1 5:58:52</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:08:30</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190710160254564614</td>\n",
       "      <td>2019/7/10 8:18:32</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>2019/10/7 3:36:05</td>\n",
       "      <td>2019/11/8 9:53:44</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/10 2:31:49</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190710171747569754</td>\n",
       "      <td>2019/7/10 10:09:00</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>2019/10/4 8:28:59</td>\n",
       "      <td>2019/11/4 4:01:35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:31:33</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20190709103530506511</td>\n",
       "      <td>2019/7/9 2:46:12</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>2019/10/8 2:30:07</td>\n",
       "      <td>2019/11/8 7:43:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/9 2:55:02</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190721162922166114</td>\n",
       "      <td>2019/7/21 8:35:33</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>2019/11/8 7:21:38</td>\n",
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       "      <td>2019/8/8 1:07:42</td>\n",
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       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>江苏省</td>\n",
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       "      <td>2019/7/21 8:07:06</td>\n",
       "      <td>WEIXIN</td>\n",
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       "      <td>2019/11/8 7:21:36</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 12:12:22</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190723180922255352</td>\n",
       "      <td>2019/7/23 10:18:47</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>2019/10/6 1:44:37</td>\n",
       "      <td>2019/11/5 3:05:16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:35:49</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190721154914162678</td>\n",
       "      <td>2019/7/21 8:06:47</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>2019/10/7 3:36:37</td>\n",
       "      <td>2019/11/8 7:47:43</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/7/21 8:27:12</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190721160519163776</td>\n",
       "      <td>2019/7/21 8:40:30</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>2019/10/5 9:15:57</td>\n",
       "      <td>2019/11/6 3:50:51</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 8:35:14</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190721130930151908</td>\n",
       "      <td>2019/7/21 5:38:03</td>\n",
       "      <td>ZHAOLIAN</td>\n",
       "      <td>2019/10/8 4:07:04</td>\n",
       "      <td>2019/11/8 8:15:14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 2:52:59</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190723135208238845</td>\n",
       "      <td>2019/7/23 6:27:03</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>2019/10/4 12:59:39</td>\n",
       "      <td>2019/11/4 8:44:57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/4 2:59:48</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>浙江省</td>\n",
       "      <td>20190723123655235176</td>\n",
       "      <td>2019/7/23 4:50:29</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>2019/10/7 3:16:02</td>\n",
       "      <td>2019/11/8 7:48:06</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 2:14:54</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>江苏省</td>\n",
       "      <td>20190722182431215485</td>\n",
       "      <td>2019/7/22 10:30:58</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/10/3 4:52:52</td>\n",
       "      <td>2019/11/3 2:38:04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/3 2:15:49</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>重庆市</td>\n",
       "      <td>20190725170738340757</td>\n",
       "      <td>2019/7/25 23:44:21</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>2019/10/5 2:42:54</td>\n",
       "      <td>2019/11/5 2:37:39</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/8/8 1:08:08</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>201908.0</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>湖北省</td>\n",
       "      <td>20190816161850420392</td>\n",
       "      <td>2019/8/16 8:37:22</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>2019/8/16 8:49:50</td>\n",
       "      <td>2019/11/2 20:12:16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20190816153930417024</td>\n",
       "      <td>2019/8/16 8:28:09</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>2019/8/16 8:31:09</td>\n",
       "      <td>2019/11/4 10:25:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422180</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191019145619416121</td>\n",
       "      <td>2019/10/19 7:07:29</td>\n",
       "      <td>HUABEIPLEDGE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:08:10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422181</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20191021185500480227</td>\n",
       "      <td>2019/10/21 11:03:46</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 11:09:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422182</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191021113013462330</td>\n",
       "      <td>2019/10/21 3:49:29</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 11:08:59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422183</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191021110449461234</td>\n",
       "      <td>2019/10/21 3:12:02</td>\n",
       "      <td>HUABEIPLEDGE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:08:16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422184</th>\n",
       "      <td>四川省</td>\n",
       "      <td>20191020120306437534</td>\n",
       "      <td>2019/10/20 4:18:00</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/31 23:41:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422185</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191019111942406537</td>\n",
       "      <td>2019/10/19 3:23:41</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/3 10:10:08</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422186</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191019125426411003</td>\n",
       "      <td>2019/10/19 5:07:25</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/19 5:14:41</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422187</th>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>20191020180128453018</td>\n",
       "      <td>2019/10/20 10:52:14</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/6 4:21:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422188</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>20191020175622452763</td>\n",
       "      <td>2019/10/20 10:04:02</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/6 12:13:16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422189</th>\n",
       "      <td>福建省</td>\n",
       "      <td>20191019164005422037</td>\n",
       "      <td>2019/10/19 8:50:31</td>\n",
       "      <td>YUANDONGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/4 9:03:34</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422190</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191021101548459078</td>\n",
       "      <td>2019/10/21 2:24:57</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/4 10:39:04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422191</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191022121545490343</td>\n",
       "      <td>2019/10/22 4:23:28</td>\n",
       "      <td>HUABEIPLEDGE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:08:20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422192</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191018134837384635</td>\n",
       "      <td>2019/10/18 6:00:52</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 11:08:05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422193</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>20191021085944457003</td>\n",
       "      <td>2019/10/21 8:22:16</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:23:01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422194</th>\n",
       "      <td>甘肃省</td>\n",
       "      <td>20191019180734425989</td>\n",
       "      <td>2019/10/19 10:12:20</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/10 11:08:04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422195</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191017102908346993</td>\n",
       "      <td>2019/10/17 4:52:59</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/17 5:03:32</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422196</th>\n",
       "      <td>天津市</td>\n",
       "      <td>20191017135927356246</td>\n",
       "      <td>2019/10/17 6:35:22</td>\n",
       "      <td>TIANCHENGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/3 20:50:12</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422197</th>\n",
       "      <td>福建省</td>\n",
       "      <td>20191016114253323676</td>\n",
       "      <td>2019/10/16 3:57:49</td>\n",
       "      <td>YUANDONGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/3 4:22:53</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422198</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191017154406361489</td>\n",
       "      <td>2019/10/17 7:50:36</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 1:39:11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422199</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191016163729336563</td>\n",
       "      <td>2019/10/16 8:43:19</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/4 4:32:57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422200</th>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>20191018115126379941</td>\n",
       "      <td>2019/10/18 3:57:45</td>\n",
       "      <td>DUMIAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/6 14:21:23</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422201</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191016112039322461</td>\n",
       "      <td>2019/10/16 3:36:55</td>\n",
       "      <td>HUABEIPLEDGE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:07:57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422202</th>\n",
       "      <td>海南省</td>\n",
       "      <td>20191018180512396895</td>\n",
       "      <td>2019/10/18 10:19:02</td>\n",
       "      <td>YUANDONGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/5 8:55:59</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422203</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191016162229335773</td>\n",
       "      <td>2019/10/16 8:25:27</td>\n",
       "      <td>YUEBAO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:27:58</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422204</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191018103755375962</td>\n",
       "      <td>2019/10/18 3:04:00</td>\n",
       "      <td>FENQICHAOREN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/18 3:14:45</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422205</th>\n",
       "      <td>广东省</td>\n",
       "      <td>20191017171217366146</td>\n",
       "      <td>2019/10/17 9:17:55</td>\n",
       "      <td>HUABEIPLEDGE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/8 10:08:04</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422206</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191012150533224810</td>\n",
       "      <td>2019/10/16 10:47:17</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/16 10:54:46</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422207</th>\n",
       "      <td>海南省</td>\n",
       "      <td>20191016212559343457</td>\n",
       "      <td>2019/10/16 14:15:02</td>\n",
       "      <td>WEIXIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/11/5 7:05:31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422208</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191018185324398245</td>\n",
       "      <td>2019/10/18 11:06:30</td>\n",
       "      <td>MASHANGXIAOJIN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/18 11:08:03</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422209</th>\n",
       "      <td>陕西省</td>\n",
       "      <td>20191017111841349487</td>\n",
       "      <td>2019/10/17 3:34:42</td>\n",
       "      <td>YUANDONGRONGZU</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2019/10/17 3:35:21</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>CLEAR</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>422210 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       ACCEPT_AREA_NAME            ACCOUNT_ID        COMPLETE_TIME  \\\n",
       "0                   广东省  20190814123703316430    2019/8/14 5:43:44   \n",
       "1                   江苏省  20190814145655323471    2019/8/14 7:22:06   \n",
       "2                   广东省  20190814154548326747    2019/8/14 8:07:04   \n",
       "3                   江苏省  20190813210540300579   2019/8/13 13:30:56   \n",
       "4                内蒙古自治区  20190812164942249491    2019/8/14 1:07:21   \n",
       "5                   湖北省  20190813190543297387   2019/8/13 11:26:16   \n",
       "6              新疆维吾尔自治区  20190813115208272059    2019/8/13 4:45:42   \n",
       "7                   江苏省  20190813111552269379    2019/8/13 3:36:26   \n",
       "8                   广东省  20190812143043240332    2019/8/12 7:23:31   \n",
       "9                   江苏省  20190812161211246748    2019/8/12 9:02:03   \n",
       "10                  广东省  20190811173211212918   2019/8/11 10:10:09   \n",
       "11                  江苏省  20190811170357210945    2019/8/11 9:08:28   \n",
       "12                  浙江省  20190708140722479876     2019/7/8 6:49:56   \n",
       "13                  重庆市  20190707190815458746    2019/7/7 11:25:09   \n",
       "14                  四川省  20190709110351508498     2019/7/9 3:38:39   \n",
       "15                  浙江省  20190710160254564614    2019/7/10 8:18:32   \n",
       "16                  江苏省  20190710171747569754   2019/7/10 10:09:00   \n",
       "17             新疆维吾尔自治区  20190709103530506511     2019/7/9 2:46:12   \n",
       "18                  江苏省  20190721162922166114    2019/7/21 8:35:33   \n",
       "19                  江苏省  20190721153743161719    2019/7/21 8:07:06   \n",
       "20                  重庆市  20190723180922255352   2019/7/23 10:18:47   \n",
       "21                  浙江省  20190721154914162678    2019/7/21 8:06:47   \n",
       "22                  广东省  20190721160519163776    2019/7/21 8:40:30   \n",
       "23                  湖北省  20190721130930151908    2019/7/21 5:38:03   \n",
       "24                  广东省  20190723135208238845    2019/7/23 6:27:03   \n",
       "25                  浙江省  20190723123655235176    2019/7/23 4:50:29   \n",
       "26                  江苏省  20190722182431215485   2019/7/22 10:30:58   \n",
       "27                  重庆市  20190725170738340757   2019/7/25 23:44:21   \n",
       "28                  湖北省  20190816161850420392    2019/8/16 8:37:22   \n",
       "29                  广东省  20190816153930417024    2019/8/16 8:28:09   \n",
       "...                 ...                   ...                  ...   \n",
       "422180              广东省  20191019145619416121   2019/10/19 7:07:29   \n",
       "422181              四川省  20191021185500480227  2019/10/21 11:03:46   \n",
       "422182              陕西省  20191021113013462330   2019/10/21 3:49:29   \n",
       "422183              广东省  20191021110449461234   2019/10/21 3:12:02   \n",
       "422184              四川省  20191020120306437534   2019/10/20 4:18:00   \n",
       "422185              陕西省  20191019111942406537   2019/10/19 3:23:41   \n",
       "422186              陕西省  20191019125426411003   2019/10/19 5:07:25   \n",
       "422187         新疆维吾尔自治区  20191020180128453018  2019/10/20 10:52:14   \n",
       "422188          宁夏回族自治区  20191020175622452763  2019/10/20 10:04:02   \n",
       "422189              福建省  20191019164005422037   2019/10/19 8:50:31   \n",
       "422190              陕西省  20191021101548459078   2019/10/21 2:24:57   \n",
       "422191              广东省  20191022121545490343   2019/10/22 4:23:28   \n",
       "422192              陕西省  20191018134837384635   2019/10/18 6:00:52   \n",
       "422193              甘肃省  20191021085944457003   2019/10/21 8:22:16   \n",
       "422194              甘肃省  20191019180734425989  2019/10/19 10:12:20   \n",
       "422195              陕西省  20191017102908346993   2019/10/17 4:52:59   \n",
       "422196              天津市  20191017135927356246   2019/10/17 6:35:22   \n",
       "422197              福建省  20191016114253323676   2019/10/16 3:57:49   \n",
       "422198              广东省  20191017154406361489   2019/10/17 7:50:36   \n",
       "422199              广东省  20191016163729336563   2019/10/16 8:43:19   \n",
       "422200          宁夏回族自治区  20191018115126379941   2019/10/18 3:57:45   \n",
       "422201              广东省  20191016112039322461   2019/10/16 3:36:55   \n",
       "422202              海南省  20191018180512396895  2019/10/18 10:19:02   \n",
       "422203              广东省  20191016162229335773   2019/10/16 8:25:27   \n",
       "422204              陕西省  20191018103755375962   2019/10/18 3:04:00   \n",
       "422205              广东省  20191017171217366146   2019/10/17 9:17:55   \n",
       "422206              陕西省  20191012150533224810  2019/10/16 10:47:17   \n",
       "422207              海南省  20191016212559343457  2019/10/16 14:15:02   \n",
       "422208              陕西省  20191018185324398245  2019/10/18 11:06:30   \n",
       "422209              陕西省  20191017111841349487   2019/10/17 3:34:42   \n",
       "\n",
       "              CREDIT_BY        REPAY_TIME10         REPAY_TIME11 REPAY_TIME5  \\\n",
       "0                WEIXIN                 NaN                  NaN         NaN   \n",
       "1                WEIXIN  2019/10/3 23:24:50   2019/11/8 10:33:50         NaN   \n",
       "2       TIANCHENGRONGZU  2019/10/4 12:07:01   2019/11/8 10:15:46         NaN   \n",
       "3                WEIXIN   2019/10/4 1:10:51   2019/11/3 15:53:29         NaN   \n",
       "4       TIANCHENGRONGZU   2019/10/5 5:11:38   2019/11/4 21:23:04         NaN   \n",
       "5       TIANCHENGRONGZU  2019/10/2 19:36:40   2019/11/2 20:11:04         NaN   \n",
       "6       TIANCHENGRONGZU   2019/10/8 1:47:42   2019/11/8 10:15:40         NaN   \n",
       "7                WEIXIN  2019/10/3 14:42:14    2019/11/4 5:34:28         NaN   \n",
       "8                WEIXIN   2019/10/8 2:00:48    2019/11/8 7:23:40         NaN   \n",
       "9                WEIXIN   2019/10/4 7:16:02    2019/11/4 2:28:00         NaN   \n",
       "10       MASHANGXIAOJIN  2019/8/11 10:11:22   2019/11/8 13:59:55         NaN   \n",
       "11               WEIXIN  2019/10/3 22:06:22   2019/11/3 12:29:50         NaN   \n",
       "12               DUMIAO  2019/10/10 2:07:39    2019/11/8 7:42:58         NaN   \n",
       "13               WEIXIN   2019/10/8 1:57:58    2019/11/6 1:44:08         NaN   \n",
       "14       MASHANGXIAOJIN  2019/10/1 10:12:16    2019/11/1 5:58:52         NaN   \n",
       "15               DUMIAO   2019/10/7 3:36:05    2019/11/8 9:53:44         NaN   \n",
       "16      TIANCHENGRONGZU   2019/10/4 8:28:59    2019/11/4 4:01:35         NaN   \n",
       "17               DUMIAO   2019/10/8 2:30:07    2019/11/8 7:43:03         NaN   \n",
       "18               WEIXIN   2019/10/8 1:59:16    2019/11/8 7:21:38         NaN   \n",
       "19               WEIXIN  2019/10/3 15:45:22    2019/11/8 7:21:36         NaN   \n",
       "20      TIANCHENGRONGZU   2019/10/6 1:44:37    2019/11/5 3:05:16         NaN   \n",
       "21               DUMIAO   2019/10/7 3:36:37    2019/11/8 7:47:43         NaN   \n",
       "22      TIANCHENGRONGZU   2019/10/5 9:15:57    2019/11/6 3:50:51         NaN   \n",
       "23             ZHAOLIAN   2019/10/8 4:07:04    2019/11/8 8:15:14         NaN   \n",
       "24      TIANCHENGRONGZU  2019/10/4 12:59:39    2019/11/4 8:44:57         NaN   \n",
       "25               DUMIAO   2019/10/7 3:16:02    2019/11/8 7:48:06         NaN   \n",
       "26               WEIXIN   2019/10/3 4:52:52    2019/11/3 2:38:04         NaN   \n",
       "27               WEIXIN   2019/10/5 2:42:54    2019/11/5 2:37:39         NaN   \n",
       "28      TIANCHENGRONGZU   2019/8/16 8:49:50   2019/11/2 20:12:16         NaN   \n",
       "29      TIANCHENGRONGZU   2019/8/16 8:31:09   2019/11/4 10:25:00         NaN   \n",
       "...                 ...                 ...                  ...         ...   \n",
       "422180     HUABEIPLEDGE                 NaN   2019/11/8 10:08:10         NaN   \n",
       "422181     FENQICHAOREN                 NaN   2019/11/8 11:09:03         NaN   \n",
       "422182     FENQICHAOREN                 NaN   2019/11/8 11:08:59         NaN   \n",
       "422183     HUABEIPLEDGE                 NaN   2019/11/8 10:08:16         NaN   \n",
       "422184  TIANCHENGRONGZU                 NaN  2019/10/31 23:41:00         NaN   \n",
       "422185     FENQICHAOREN                 NaN   2019/11/3 10:10:08         NaN   \n",
       "422186     FENQICHAOREN                 NaN   2019/10/19 5:14:41         NaN   \n",
       "422187           DUMIAO                 NaN    2019/11/6 4:21:03         NaN   \n",
       "422188   MASHANGXIAOJIN                 NaN   2019/11/6 12:13:16         NaN   \n",
       "422189   YUANDONGRONGZU                 NaN    2019/11/4 9:03:34         NaN   \n",
       "422190           WEIXIN                 NaN   2019/11/4 10:39:04         NaN   \n",
       "422191     HUABEIPLEDGE                 NaN   2019/11/8 10:08:20         NaN   \n",
       "422192     FENQICHAOREN                 NaN   2019/11/8 11:08:05         NaN   \n",
       "422193  TIANCHENGRONGZU                 NaN   2019/11/8 10:23:01         NaN   \n",
       "422194  TIANCHENGRONGZU                 NaN  2019/11/10 11:08:04         NaN   \n",
       "422195     FENQICHAOREN                 NaN   2019/10/17 5:03:32         NaN   \n",
       "422196  TIANCHENGRONGZU                 NaN   2019/11/3 20:50:12         NaN   \n",
       "422197   YUANDONGRONGZU                 NaN    2019/11/3 4:22:53         NaN   \n",
       "422198           WEIXIN                 NaN    2019/11/8 1:39:11         NaN   \n",
       "422199   MASHANGXIAOJIN                 NaN    2019/11/4 4:32:57         NaN   \n",
       "422200           DUMIAO                 NaN   2019/11/6 14:21:23         NaN   \n",
       "422201     HUABEIPLEDGE                 NaN   2019/11/8 10:07:57         NaN   \n",
       "422202   YUANDONGRONGZU                 NaN    2019/11/5 8:55:59         NaN   \n",
       "422203           YUEBAO                 NaN   2019/11/8 10:27:58         NaN   \n",
       "422204     FENQICHAOREN                 NaN   2019/10/18 3:14:45         NaN   \n",
       "422205     HUABEIPLEDGE                 NaN   2019/11/8 10:08:04         NaN   \n",
       "422206           WEIXIN                 NaN  2019/10/16 10:54:46         NaN   \n",
       "422207           WEIXIN                 NaN    2019/11/5 7:05:31         NaN   \n",
       "422208   MASHANGXIAOJIN                 NaN  2019/10/18 11:08:03         NaN   \n",
       "422209   YUANDONGRONGZU                 NaN   2019/10/17 3:35:21         NaN   \n",
       "\n",
       "       REPAY_TIME6 REPAY_TIME7        REPAY_TIME8  ... SEASON7   SEASON8  \\\n",
       "0              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "1              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "2              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "3              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "4              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "5              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "6              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "7              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "8              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "9              NaN         NaN                NaN  ...     NaN       NaN   \n",
       "10             NaN         NaN                NaN  ...     NaN       NaN   \n",
       "11             NaN         NaN                NaN  ...     NaN       NaN   \n",
       "12             NaN         NaN   2019/8/8 2:10:27  ...     NaN  201908.0   \n",
       "13             NaN         NaN   2019/8/8 1:06:16  ...     NaN  201908.0   \n",
       "14             NaN         NaN   2019/8/8 8:08:30  ...     NaN  201908.0   \n",
       "15             NaN         NaN  2019/8/10 2:31:49  ...     NaN  201908.0   \n",
       "16             NaN         NaN   2019/8/8 8:31:33  ...     NaN  201908.0   \n",
       "17             NaN         NaN   2019/7/9 2:55:02  ...     NaN  201908.0   \n",
       "18             NaN         NaN   2019/8/8 1:07:42  ...     NaN  201908.0   \n",
       "19             NaN         NaN  2019/8/3 12:12:22  ...     NaN  201908.0   \n",
       "20             NaN         NaN   2019/8/8 8:35:49  ...     NaN  201908.0   \n",
       "21             NaN         NaN  2019/7/21 8:27:12  ...     NaN  201908.0   \n",
       "22             NaN         NaN   2019/8/8 8:35:14  ...     NaN  201908.0   \n",
       "23             NaN         NaN   2019/8/8 2:52:59  ...     NaN  201908.0   \n",
       "24             NaN         NaN   2019/8/4 2:59:48  ...     NaN  201908.0   \n",
       "25             NaN         NaN   2019/8/8 2:14:54  ...     NaN  201908.0   \n",
       "26             NaN         NaN   2019/8/3 2:15:49  ...     NaN  201908.0   \n",
       "27             NaN         NaN   2019/8/8 1:08:08  ...     NaN  201908.0   \n",
       "28             NaN         NaN                NaN  ...     NaN       NaN   \n",
       "29             NaN         NaN                NaN  ...     NaN       NaN   \n",
       "...            ...         ...                ...  ...     ...       ...   \n",
       "422180         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422181         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422182         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422183         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422184         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422185         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422186         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422187         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422188         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422189         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422190         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422191         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422192         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422193         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422194         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422195         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422196         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422197         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422198         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422199         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422200         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422201         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422202         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422203         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422204         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422205         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422206         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422207         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422208         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "422209         NaN         NaN                NaN  ...     NaN       NaN   \n",
       "\n",
       "        STATUS10  STATUS11  STATUS5 STATUS6 STATUS7 STATUS8 STATUS9 USER_TYPE  \n",
       "0           OPEN      OPEN      NaN     NaN     NaN     NaN    OPEN         2  \n",
       "1          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "2          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "3          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "4          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "5          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "6          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "7          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "8          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "9          CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "10         CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "11         CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "12         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "13         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "14         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "15         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "16         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "17         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "18         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "19         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "20         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "21         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "22         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "23         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "24         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "25         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "26         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "27         CLEAR     CLEAR      NaN     NaN     NaN   CLEAR   CLEAR         2  \n",
       "28         CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         1  \n",
       "29         CLEAR     CLEAR      NaN     NaN     NaN     NaN   CLEAR         2  \n",
       "...          ...       ...      ...     ...     ...     ...     ...       ...  \n",
       "422180       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN        12  \n",
       "422181       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422182       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422183       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN        12  \n",
       "422184       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         1  \n",
       "422185       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422186       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422187       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422188       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422189       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422190       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422191       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN        12  \n",
       "422192       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422193       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         1  \n",
       "422194       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         1  \n",
       "422195       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422196       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         1  \n",
       "422197       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422198       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422199       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422200       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422201       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN        12  \n",
       "422202       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422203       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN        10  \n",
       "422204       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422205       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN        12  \n",
       "422206       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422207       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422208       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "422209       NaN     CLEAR      NaN     NaN     NaN     NaN     NaN         2  \n",
       "\n",
       "[422210 rows x 23 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "\n",
    "# 指定工作目录路径\n",
    "os.chdir('D:\\迁移率')\n",
    "data = pd.read_csv('order_repay.csv',low_memory=False)\n",
    "data1 = data.drop(columns='记录数')\n",
    "data=data1.copy()\n",
    "name = list(data)\n",
    "# 把列名转为大写\n",
    "for n in name:\n",
    "#     print(n.upper())\n",
    "    data.rename(columns={n:n.upper()},inplace=True)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-11-11T08:54:14.151165Z",
     "start_time": "2019-11-11T08:42:00.046854Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "迁移率数据写入完成！文件位置:D:\\迁移率\n"
     ]
    }
   ],
   "source": [
    "\n",
    "grant = ['ZHONGAN', 'ZHAOLIAN', 'MASHANGXIAOJIN', 'WEIXIN', 'ZIZHUSHOUXIN', 'BESTPAY', 'GUOFU',\n",
    "         'DUMIAO', 'FENQICHAOREN', 'ZIYING', 'TIANCHENGRONGZU', 'YUANDONGRONGZU', 'HUABEIPLEDGE']\n",
    "user = [1, 2, 3, 4, 5, 10, 12]\n",
    "area = [\"广东省\", \"江苏省\", \"重庆市\", \"四川省\", \"新疆维吾尔自治区\", \"浙江省\", \"内蒙古自治区\", \"湖北省\", \"辽宁省\",\"陕西省\",\"海南省\",\"山西省\",\"福建省\",\"甘肃省\",\"天津市\",\"宁夏回族自治区\"]\n",
    "\n",
    "\n",
    "# 计算逾期期数\n",
    "# x:series y:账期数\n",
    "def overdue_num(x, y):\n",
    "    o_num = 0\n",
    "    for i in range(5, y + 1):\n",
    "        o_num = o_num + int(x['STATUS' + str(i)] == 'OPEN') + int(\n",
    "            x['REPAY_TIME' + str(i)] >= pd.to_datetime('2019-' + str(y+1) + '-1'))\n",
    "    return o_num\n",
    "\n",
    "\n",
    "for i in grant:\n",
    "    for j in user:\n",
    "        for k in area:\n",
    "            all = data.loc[(data['CREDIT_BY'] == i) & (data['USER_TYPE'] == j) & (data['ACCEPT_AREA_NAME'] == k)].copy()\n",
    "            if all.shape[0] == 0:\n",
    "                pass\n",
    "            else:\n",
    "                #                 print(all.shape)\n",
    "\n",
    "                # 转换时间\n",
    "                all['REPAY_TIME5'] = pd.to_datetime(all.REPAY_TIME5, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME6'] = pd.to_datetime(all.REPAY_TIME6, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME7'] = pd.to_datetime(all.REPAY_TIME7, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME8'] = pd.to_datetime(all.REPAY_TIME8, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME9'] = pd.to_datetime(all.REPAY_TIME9, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME10'] = pd.to_datetime(all.REPAY_TIME10, format='%Y-%m-%d')\n",
    "                all['REPAY_TIME11'] = pd.to_datetime(all.REPAY_TIME11, format='%Y-%m-%d')\n",
    "                all['COMPLETE_TIME'] = pd.to_datetime(all.COMPLETE_TIME, format='%Y-%m-%d').dt.month\n",
    "                # 按完成时间分类\n",
    "                m4 = all[all['COMPLETE_TIME'] == 4]\n",
    "                m5 = all[all['COMPLETE_TIME'] == 5]\n",
    "                m6 = all[all['COMPLETE_TIME'] == 6]\n",
    "                m7 = all[all['COMPLETE_TIME'] == 7]\n",
    "                m8 = all[all['COMPLETE_TIME'] == 8]\n",
    "                m9 = all[all['COMPLETE_TIME'] == 9]\n",
    "                m10 = all[all['COMPLETE_TIME'] == 10]\n",
    "                m11 = all[all['COMPLETE_TIME'] == 11]\n",
    "                # 4月\n",
    "                # 按mob分类\n",
    "                # 4月完成\n",
    "                list_all_c_4 = list(m4['ACCOUNT_ID'])\n",
    "                # 5月\n",
    "                # 按mob分类\n",
    "                # 4月完成\n",
    "                list_m4_t_5 = list(m4[m4['STATUS5'] == 'TERMINATE']['ACCOUNT_ID']) + list(\n",
    "                    m4[m4['STATUS5'] == 'CLOSE']['ACCOUNT_ID'])\n",
    "                list_m4_m1_5 = list(m4[m4['STATUS5'] == 'OPEN']['ACCOUNT_ID']) + list(\n",
    "                    m4[m4['REPAY_TIME5'] >= '2019-6-1']['ACCOUNT_ID'])\n",
    "                list_m4_c_5 = list(set(m4['ACCOUNT_ID']) ^ set(list_m4_t_5 + list_m4_m1_5))\n",
    "\n",
    "                # 总的\n",
    "                list_all_t_5 = list_m4_t_5\n",
    "                list_all_m1_5 = list_m4_m1_5\n",
    "\n",
    "                list_all_c_5 = list_m4_c_5 + list(m5['ACCOUNT_ID'])\n",
    "\n",
    "                # 6月\n",
    "                # 取4月和五月完成的数据\n",
    "                m4_5 = all[all['COMPLETE_TIME'].isin(list(range(4, 6)))].copy()\n",
    "                if m4_5.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_5['overdue_num'] = m4_5.apply(lambda x: overdue_num(x=x, y=6), axis=1)\n",
    "                else:\n",
    "                    m4_5['overdue_num'] = 0\n",
    "                list_all_m1_6 = list(m4_5[m4_5['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_6 = list(m4_5[m4_5['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_c_6 = list(\n",
    "                    m4_5.loc[(m4_5['STATUS6'] == 'CLEAR') & (m4_5['REPAY_TIME6'] < '2019-7-1')]['ACCOUNT_ID']) + list(\n",
    "                    m6['ACCOUNT_ID'])\n",
    "\n",
    "                # 7月\n",
    "                # 取4-6月完成的数据\n",
    "                m4_6 = all[all['COMPLETE_TIME'].isin(list(range(4, 7)))].copy()\n",
    "                if m4_6.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_6['overdue_num'] = m4_6.apply(lambda x: overdue_num(x=x, y=7), axis=1)\n",
    "                else:\n",
    "                    m4_6['overdue_num'] = 0\n",
    "                list_all_m1_7 = list(m4_6[m4_6['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_7 = list(m4_6[m4_6['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_7 = list(m4_6[m4_6['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_c_7 = list(\n",
    "                    m4_6.loc[(m4_6['STATUS7'] == 'CLEAR') & (m4_6['REPAY_TIME7'] < '2019-8-1')]['ACCOUNT_ID']) + list(\n",
    "                    m7['ACCOUNT_ID'])\n",
    "\n",
    "                # 8月\n",
    "                # 取4-7月完成的数据\n",
    "                m4_7 = all[all['COMPLETE_TIME'].isin(list(range(4, 8)))].copy()\n",
    "                if m4_7.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_7['overdue_num'] = m4_7.apply(lambda x: overdue_num(x=x, y=8), axis=1)\n",
    "                else:\n",
    "                    m4_7['overdue_num'] = 0\n",
    "                list_all_m1_8 = list(m4_7[m4_7['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_8 = list(m4_7[m4_7['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_8 = list(m4_7[m4_7['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_m4_8 = list(m4_7[m4_7['overdue_num'] == 4]['ACCOUNT_ID'])\n",
    "                list_all_c_8 = list(\n",
    "                    m4_7.loc[(m4_7['STATUS8'] == 'CLEAR') & (m4_7['REPAY_TIME8'] < '2019-9-1')]['ACCOUNT_ID']) + list(\n",
    "                    m8['ACCOUNT_ID'])\n",
    "\n",
    "                # 9月\n",
    "                # 取4-8月完成的数据\n",
    "                m4_8 = all[all['COMPLETE_TIME'].isin(list(range(4, 9)))].copy()\n",
    "                if m4_8.shape[0] > 0:\n",
    "                    # 判断逾期几期并记录到dataframe\n",
    "                    m4_8['overdue_num'] = m4_8.apply(lambda x: overdue_num(x=x, y=9), axis=1)\n",
    "                else:\n",
    "                    m4_8['overdue_num'] = 0\n",
    "                list_all_m1_9 = list(m4_8[m4_8['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_9 = list(m4_8[m4_8['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_9 = list(m4_8[m4_8['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_m4_9 = list(m4_8[m4_8['overdue_num'] == 4]['ACCOUNT_ID'])\n",
    "                list_all_m5_9 = list(m4_8[m4_8['overdue_num'] == 5]['ACCOUNT_ID'])\n",
    "                list_all_c_9 = list(\n",
    "                    m4_8.loc[(m4_8['STATUS9'] == 'CLEAR') & (m4_8['REPAY_TIME9'] < '2019-10-1')]['ACCOUNT_ID']) + list(\n",
    "                    m9['ACCOUNT_ID'])\n",
    "\n",
    "                # 10月\n",
    "                # 取4-9月完成的数据\n",
    "                m4_9 = all[all['COMPLETE_TIME'].isin(list(range(4, 10)))].copy()\n",
    "                if m4_9.shape[0] > 0:\n",
    "                     # 判断逾期几期并记录到dataframe\n",
    "                    m4_9['overdue_num'] = m4_9.apply(lambda x: overdue_num(x=x, y=10), axis=1)\n",
    "                else:\n",
    "                     m4_9['overdue_num'] = 0\n",
    "                list_all_m1_10 = list(m4_9[m4_9['overdue_num'] == 1]['ACCOUNT_ID'])\n",
    "                list_all_m2_10 = list(m4_9[m4_9['overdue_num'] == 2]['ACCOUNT_ID'])\n",
    "                list_all_m3_10 = list(m4_9[m4_9['overdue_num'] == 3]['ACCOUNT_ID'])\n",
    "                list_all_m4_10 = list(m4_9[m4_9['overdue_num'] == 4]['ACCOUNT_ID'])\n",
    "                list_all_m5_10 = list(m4_9[m4_9['overdue_num'] == 5]['ACCOUNT_ID'])\n",
    "                list_all_m6_10 = list(m4_9[m4_9['overdue_num'] == 6]['ACCOUNT_ID'])\n",
    "                list_all_c_10 = list(\n",
    "                     m4_9.loc[(m4_9['STATUS10'] == 'CLEAR') & (m4_9['REPAY_TIME10'] < '2019-11-1')]['ACCOUNT_ID']) + list(\n",
    "                     m10['ACCOUNT_ID'])\n",
    "\n",
    "\n",
    "                # 计算结果保存\n",
    "                with open('迁移率(月底)导出.txt', 'a+') as f:\n",
    "                    # C-M1\n",
    "                    for m in range(5, 11):\n",
    "                        fz = len(set(eval('list_all_m1_' + str(m))) & set(eval('list_all_c_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_c_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},C-M1,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M1-M2\n",
    "                    for m in range(6, 11):\n",
    "                        fz = len(set(eval('list_all_m2_' + str(m))) & set(eval('list_all_m1_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m1_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M1-M2,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M2-M3\n",
    "                    for m in range(7, 11):\n",
    "                        fz = len(set(eval('list_all_m3_' + str(m))) & set(eval('list_all_m2_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m2_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M2-M3,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M3-M4\n",
    "                    for m in range(8, 11):\n",
    "                        fz = len(set(eval('list_all_m4_' + str(m))) & set(eval('list_all_m3_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m3_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M3-M4,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M4-M5\n",
    "                    for m in range(9, 11):\n",
    "                        fz = len(set(eval('list_all_m5_' + str(m))) & set(eval('list_all_m4_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m4_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M4-M5,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M5-M6\n",
    "                    for m in range(10, 11):\n",
    "                        fz = len(set(eval('list_all_m6_' + str(m))) & set(eval('list_all_m5_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m5_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M5-M6,2019{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # C-M2\n",
    "                    #                     for m in range(6,10):\n",
    "                    #                         c_m1_z = len(set(eval('list_all_m1_'+str(m-1))) & set(eval('list_all_c_'+str(m-2))))\n",
    "                    #                         c_m1_m = len(eval('list_all_c_'+str(m-2)))\n",
    "                    #                         m1_m2_z = len(eval('list_all_m2_'+str(m)))\n",
    "                    #                         m1_m2_m = len(eval('list_all_m1_'+str(m-1)))\n",
    "                    #                         fz = c_m1_z * m1_m2_z\n",
    "                    #                         fm = c_m1_m * m1_m2_m\n",
    "                    #                         f.write(\"{},{},{},C-M2,20190{},{},{}\".format(i, j, k, m,fz, fm) + '\\n')\n",
    "\n",
    "                    # C-M3\n",
    "                    #                     for m in range(7,10):\n",
    "                    #                         c_m1_z = len(set(eval('list_all_m1_'+str(m-2))) & set(eval('list_all_c_'+str(m-3))))\n",
    "                    #                         c_m1_m = len(eval('list_all_c_'+str(m-3)))\n",
    "                    #                         m1_m2_m = len(eval('list_all_m1_'+str(m-2)))\n",
    "                    #                         m2_m3_z = len(eval('list_all_m3_'+str(m)))\n",
    "                    #                         fz = c_m1_z * m2_m3_z\n",
    "                    #                         fm = c_m1_m * m1_m2_m\n",
    "                    #                         f.write(\"{},{},{},C-M3,20190{},{},{}\".format(i, j, k, m,fz, fm) + '\\n')\n",
    "\n",
    "                    # C-M4\n",
    "                    #                     for m in range(8,10):\n",
    "                    #                         c_m1_z = len(set(eval('list_all_m1_'+str(m-3))) & set(eval('list_all_c_'+str(m-4))))\n",
    "                    #                         c_m1_m = len(eval('list_all_c_'+str(m-4)))\n",
    "                    #                         m1_m2_m = len(eval('list_all_m1_'+str(m-3)))\n",
    "                    #                         m3_m4_z = len(eval('list_all_m4_'+str(m)))\n",
    "                    #                         fz = c_m1_z * m3_m4_z\n",
    "                    #                         fm = c_m1_m * m1_m2_m\n",
    "                    #                         f.write(\"{},{},{},C-M4,20190{},{},{}\".format(i, j, k, m,fz, fm) + '\\n')\n",
    "\n",
    "                    # C-M5\n",
    "                    #                     for m in range(9,10):\n",
    "                    #                         c_m1_z = len(set(eval('list_all_m1_'+str(m-4))) & set(eval('list_all_c_'+str(m-5))))\n",
    "                    #                         c_m1_m = len(eval('list_all_c_'+str(m-5)))\n",
    "                    #                         m1_m2_m = len(eval('list_all_m1_'+str(m-4)))\n",
    "                    #                         m4_m5_z = len(eval('list_all_m5_'+str(m)))\n",
    "                    #                         fz = c_m1_z * m4_m5_z\n",
    "                    #                         fm = c_m1_m * m1_m2_m\n",
    "                    #                         f.write(\"{},{},{},C-M5,20190{},{},{}\".format(i, j, k, m,fz, fm) + '\\n')\n",
    "\n",
    "                    # C-C\n",
    "                    for m in range(5, 11):\n",
    "                        fz = len(set(eval('list_all_c_' + str(m))) & set(eval('list_all_c_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_c_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},C-C,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M1-C\n",
    "                    for m in range(6, 11):\n",
    "                        fz = len(set(eval('list_all_c_' + str(m))) & set(eval('list_all_m1_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m1_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M1-C,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M2-C\n",
    "                    for m in range(7, 11):\n",
    "                        fz = len(set(eval('list_all_c_' + str(m))) & set(eval('list_all_m2_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m2_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M2-C,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M3-C\n",
    "                    for m in range(8, 11):\n",
    "                        fz = len(set(eval('list_all_c_' + str(m))) & set(eval('list_all_m3_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m3_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M3-C,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M4-C\n",
    "                    for m in range(9, 11):\n",
    "                        fz = len(set(eval('list_all_c_' + str(m))) & set(eval('list_all_m4_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m4_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M4-C,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M5-C\n",
    "                    for m in range(10, 11):\n",
    "                        fz = len(set(eval('list_all_c_' + str(m))) & set(eval('list_all_m5_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m5_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M5-C,2019{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M1-M1\n",
    "                    for m in range(6, 11):\n",
    "                        fz = len(set(eval('list_all_m1_' + str(m))) & set(eval('list_all_m1_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m1_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M1-M1,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M2-M1\n",
    "                    for m in range(7, 11):\n",
    "                        fz = len(set(eval('list_all_m1_' + str(m))) & set(eval('list_all_m2_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m2_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M2-M1,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M3-M1\n",
    "                    for m in range(8, 11):\n",
    "                        fz = len(set(eval('list_all_m1_' + str(m))) & set(eval('list_all_m3_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m3_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M3-M1,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "                    # M4-M1\n",
    "                    for m in range(9, 11):\n",
    "                        fz = len(set(eval('list_all_m1_' + str(m))) & set(eval('list_all_m4_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m4_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M4-M1,20190{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "                        \n",
    "                    # M5-M1\n",
    "                    for m in range(10, 11):\n",
    "                        fz = len(set(eval('list_all_m1_' + str(m))) & set(eval('list_all_m5_' + str(m - 1))))\n",
    "                        fm = len(eval('list_all_m5_' + str(m - 1)))\n",
    "                        f.write(\"{},{},{},M5-M1,2019{},{},{}\".format(i, j, k, m, fz, fm) + '\\n')\n",
    "\n",
    "print('迁移率数据写入完成！文件位置:{}'.format(os.getcwd()))\n"
   ]
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